Research On Wearable Intelligent Ecg Device

With the acceleration of the aging population and the urbanization process, the Chinese urban and rural residents of cardiovascular disease morbidity is on the rise. According to the statistics, cardiovascular disease mortality account for the first cause of death in urban and rural residents. Real-time monitoring of cardiac activity is of great significance for the early prevention of heart disease. However, these conventional ECG devices have many limitations. Such as these device are always bulky and prices are higher, and they are not easy to carry. Combining ECG monitoring with mobile communications technology, we developed a wearable ECG devices. This device is capable of continuously monitoring the electrical activity of the heart, making it possible for the ECG device to be gradually popular in family. This paper completed in following two parts: 1. Hardware DesignSystem hardware circuit’s design includes the ECG acquisition section and power circuit section. In terms of hardware, highly integrated, low-power components is our first choice. The design of ECG acquisition circuit applies highly integrated and low power components, selecting ADS1191 acquisition chip of TI to acquire ECG signal. The signal is transfered to the low power MSP430 microcontroller by the way of SPI. The smart ECG equipment chose a rechargeable battery, and use a new wireless charging technology for its charge. 2. Signal Intelligent AnalysisFor the intelligent analysis part, the collected ECG signal is transmit via Bluetooth 2.0 to the phone for further analysis. ECG analysis includes four steps: signal preprocessing, feature extraction,feature selection and classification of heart beat. After doing some specific treatment including filtering and de-nosing, we extract the signal related features to diagnose automatically. In this paper, AdaBoost algorithm is used to the arrhythmia analysis. And we also compare it with distance discriminant algorithm and SVM method. The results showed that Adaboost algorithm has a better classification result, its accuary is up to 98%..The wearable device ECG intelligent equipment has small size and low power-consumption,and it could monitor the ECG signal in a long time,The prototype we designed is about 11 cm, the consumption power of device without Bluetooth is only 0.98 mA, and the power consumption of Bluetooth 2.0 when it is working is 16 mA. It achieves the desired design requirements, and could be used for homecare ECG monitoring.